{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3a79ef54-63e6-429f-ba9f-590b736a7f29",
   "metadata": {},
   "source": [
    "# 4.2 在二维空间中绘制直线"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c90a18b9-d8e8-431c-856c-35f1e4ed05e1",
   "metadata": {},
   "source": [
    "### 1.任务描述\n",
    "\n",
    "一组房屋面积的数据如下（16个）:\n",
    "\n",
    "137.97,104.50,100.00,124.32,79.20,99.00,124.00,114.00,106.69,138.05,53.75,46.91,68.00,63.02,81.26,86.21。\n",
    "\n",
    "假设房屋价格和房屋面积之间是线性关系，可以通过公式求得房屋价格：$y=wx+b$。\n",
    "\n",
    "其中，x为房屋面积，y为房屋价格，w=0.8945604，b=5.4108505。\n",
    "\n",
    "要求：\n",
    "\n",
    "- 根据房屋价格的公式，求得上述房屋的价格。\n",
    "- 以面积为x轴，以价格为y轴，绘制直线。"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8d7baa9c-93a2-42f3-a3c1-231cdb587f2d",
   "metadata": {},
   "source": [
    "### 2.知识准备\n",
    "\n",
    "见教程。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74ad989a-9b82-43e1-b841-e74284cd5936",
   "metadata": {},
   "source": [
    "### 3.任务分析\n",
    "\n",
    "可使用matplotlib.pyplot.plot方法绘制直线。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "435c6090-cfda-4f46-a550-22a368e41e4a",
   "metadata": {},
   "source": [
    "### 4.任务实施\n",
    "\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "ec75eb6c-5da3-467d-a471-ca3b47242dd6",
   "metadata": {},
   "source": [
    "执行代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2ae9da58-e339-4d22-9f8d-ca255711d89e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "import numpy as np\n",
    "# 根据房屋面积数据，创建NumPy数组\n",
    "x=np.array([137.97,104.50,100.00,124.32,79.20,99.00,124.00,114.00,106.69,138.05,53.75,46.91,68.00,63.02,81.26,86.21])\n",
    "w=0.8945604  \n",
    "b=5.4108505  \n",
    "y=x*w+b\n",
    "plt.figure(figsize=(6,4))\n",
    "# 绘制直线\n",
    "plt.plot(x,y,color=\"green\",label=\"房价直线\",linewidth=1)\n",
    "# 设置图形的属性\n",
    "# x轴标签\n",
    "plt.xlabel(\"面积(平方米)\",fontsize=14)\n",
    "# y轴标签\n",
    "plt.ylabel(\"价格(万元)\",fontsize=14)\n",
    "# x轴刻度范围\n",
    "plt.xlim(40,150)\n",
    "# y轴刻度范围\n",
    "plt.ylim(40,150)\n",
    "# 图形标题\n",
    "plt.suptitle(\"商品房销售价格评估系统\",fontsize=20)\n",
    "# 显示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f2c61db-4b69-49f9-9b22-f6d2642a056d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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